Gaussian copula is by far the most popular copula used in the financial industry in default dependency modeling. However, it has a major drawback — it does not exhibit tail dependence, a very important property for copula. The essence of tail dependence is the interdependence when extreme events occur, say, defaults of corporate bonds. In this paper we show that some tail dependence can be rest...

Using one of the key property of copulas that they remain invariant under an arbitrary monotonous change of variable, we investigate the null hypothesis that the dependence between financial assets can be modeled by the Gaussian copula. We find that most pairs of currencies and pairs of major stocks are compatible with the Gaussian copula hypothesis, while this hypothesis can be rejected for th...

This paper concentrates on estimating the risk of Title Transfer Facility (TTF) Hub natural gas portfolios by using the GARCH-EVT-copula model. We first use the univariate ARMA-GARCH model to model each natural gas return series. Second, the extreme value distribution (EVT) is fitted to the tails of the residuals to model marginal residual distributions. Third, multivariate Gaussian copula and ...

Empirical copula is a non-parametric algorithm to estimate the dependence structure of highdimensional arbitrarily distributed data. The computation of empirical copula is, however, very costly so that it cannot be implemented into applications at a real-time context. In this paper, fuzzy empirical copula is proposed to reduce the computation time of dependence structure estimation. First, a br...

Copulas are full measures of dependence among components of random vectors. Unlike the marginal and the joint distributions, which are directly observable, a copula is a hidden dependence structure that couples a joint distribution with its marginals. This makes the task of proposing a parametric copula model non-trivial and is where a nonparametric estimator can play a significant role. In thi...

Copula is a function which can link two or more marginal distributions together to form a joint distribution. This paper aims to analyze the dependence between Shanghai and Shenzhen stock markets using copula theory based on GARCH. We use the synchronous 100 times daily returns data and copula based GARCH to model the joint distribution of stock index returns because copula based GARCH can fit ...

One main complexity of the copula constructions concerns a mismatch between morphology and syntactic constituency: the copula seems to form a morphological unit with the immediately preceding element, whereas in terms of syntax the copula appears to take this as its syntactic complement. In capturing such mismatches, we show that the copula is treated as an independent verb at the level of tect...

Monash Haematology, Monash Health, Clayton, Victoria, Australia Monash University School of Clinical Sciences at Monash Health, Clayton, Victoria, Australia Centre for Cancer Research, Hudson Institute of Medical Research Clayton, Victoria, Australia Immunology/Molecular Immunology Division, Walter and Eliza Hall Institute of Medical Research, Melbourne, Victoria, Australia Department of Medica...

In this review paper we outline some recent contributions to copula theory. Several new author's investigations are presented brie°y, namely: order statistics copula, copulas with given multivariate marginals, copula representation via a local dependence measure and applications of extreme value copulas. Key-words: Copula; Dependence measures; Extremes; Kendall distribution; Local dependence; M...